PROJECT SUMMARY It has become feasible to generate deep quantitative data for many of the molecules that are functional in cells, making it possible to survey a large number of tumors measuring genomic alterations and changes to transcripts, proteins and metabolites. It is, however, not clear what is the best way to integrate these data sets to extract as much information as possible about the biology that drives the cancer and how to best disrupt the tumor growth. Our proposed Proteogenomic Data Analysis Center for Cancer Systems Biology and Clinical Translation will develop new methods for better analyzing and integrating these data sets. In addition to developing statistical and machine learning methods, we also emphasize visual exploration of the data, and we will implement interactive web browser based visualization that will allow researchers to easily explore these vast data sets and gain novel insights by being able to quickly switch between summary information and details of the raw data.